Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:
The method for the research-field-mapping can be reviewed here:
The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:
The present analysis is based on the following seed articles:
| AU | PY | TI | JI |
|---|---|---|---|
| ANDRÉ CM;GUERRIERO G;LATEUR… | 2022 | IDENTIFICATION OF NOVEL CANDIDATE GENES INVOLVED IN APPLE CUTICLE INTEGRITY AND RUSSETING-ASSOCIA… | PLANTS |
| CALUSINSKA M;MARYNOWSKA M;B… | 2020 | INTEGRATIVE OMICS ANALYSIS OF THE TERMITE GUT SYSTEM ADAPTATION TO MISCANTHUS DIET IDENTIFIES LIG… | COMMUN. BIOLOG. |
| PIGNÉ Y;GUTIÉRREZ TN;GIBON … | 2020 | A TOOL TO OPERATIONALIZE DYNAMIC LCA, INCLUDING TIME DIFFERENTIATION ON THE COMPLETE BACKGROUND D… | INT. J. LIFE CYCLE ASSESS. |
| RODRIGUEZ NB;KLAUS J | 2019 | CATCHMENT TRAVEL TIMES FROM COMPOSITE STORAGE SELECTION FUNCTIONS REPRESENTING THE SUPERPOSITION … | WATER RESOUR. RES. |
| CHINI M;HOSTACHE R;PELICH R… | 2019 | PROBABILISTIC URBAN FLOOD MAPPING USING SAR DATA | DIG INT GEOSCI REMOTE SENS … |
| MOLITOR D;SCHULTZ M;FRIEDRI… | 2018 | EFFICACY OF FENHEXAMID TREATMENTS AGAINST BOTRYTIS CINEREA IN GRAPEVINE AS AFFECTED BY TIME OF AP… | CROP PROT. |
| BHATTARAI N;MALLICK K;BRUNS… | 2018 | REGIONAL EVAPOTRANSPIRATION FROM AN IMAGE-BASED IMPLEMENTATION OF THE SURFACE TEMPERATURE INITIAT… | HYDROL. EARTH SYST. SCI. |
| CAPITANESCU F | 2018 | OPF INTEGRATING DISTRIBUTION SYSTEMS FLEXIBILITY FOR TSO REAL-TIME ACTIVE POWER BALANCE MANAGEMENT | IET CONF PUBL |
| PETRI I;ALHAMAMI A;REZGUI Y… | 2018 | A VIRTUAL COLLABORATIVE PLATFORM TO SUPPORT BUILDING INFORMATION MODELING IMPLEMENTATION FOR ENER… | IFIP ADVANCES IN INFORMATIO… |
| CENCI L;PULVIRENTI L;BONI G… | 2017 | AN EVALUATION OF THE POTENTIAL OF SENTINEL 1 FOR IMPROVING FLASH FLOOD PREDICTIONS VIA SOIL MOIST… | ADV. GEOSCI. |
Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.
Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_list_erin.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.
Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.
LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.
LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.
The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.
The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.
The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.
Note: This analysis refers the co-citation analysis,
where the cited references and not the original publications are the
unit of analysis. See tab Technical descriptionfor
additional explanations
In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.
| name | dgr_int | dgr |
|---|---|---|
| Knowledge Base 1: KB 1: Evapotranspiration estimates (n = 3634, density =2.16) | ||
| SU Z. THE SURFACE ENERGY BALANCE SYSTEM (SEBS) | 9364 | 9589 |
| MU Q. ZHAO M. RUNNING S.W. IMPROVEMENTS TO A MODIS GLOBAL TERRESTRIAL EVAPOTRANSPIRATION ALGORITHM (2011) | 9340 | 9951 |
| MU Q. HEINSCH F.A. ZHAO M. RUNNING S.W. DEVELOPMENT OF A GLOBAL EVAPOTRANSPIRATION ALGORITHM BASED ON MODIS AND GLOBAL METEOROLOGY DATA (2007) | 6682 | 7014 |
| ALLEN R.G. TASUMI M. TREZZA R. SATELLITE-BASED ENERGY BALANCE FOR MAPPING EVAPOTRANSPIRATION WITH INTERNALIZED CALIBRATION (METRIC) | 5801 | 5857 |
| PRIESTLEY C.H.B. TAYLOR R.J. ON THE ASSESSMENT OF SURFACE HEAT FLUX AND EVAPORATION USING LARGE-SCALE PARAMETERS (1972) | 5201 | 5419 |
| BASTIAANSSEN W.G.M. MENENTI M. FEDDES R.A. HOLTSLAG A.A.M. A REMOTE SENSING SURFACE ENERGY BALANCE ALGORITHM FOR LAND (SEBAL) | 4857 | 4922 |
| NORMAN J.M. KUSTAS W.P. HUMES K.S. SOURCE APPROACH FOR ESTIMATING SOIL AND VEGETATION ENERGY FLUXES IN OBSERVATIONS OF DIRECTIONAL RADIOMETRIC SURF… | 4364 | 4415 |
| KALMA J.D. MCVICAR T.R. MCCABE M.F. ESTIMATING LAND SURFACE EVAPORATION: A REVIEW OF METHODS USING REMOTELY SENSED SURFACE TEMPERATURE DATA (2008) | 4110 | 4182 |
| ALLEN R.G. PEREIRA L.S. RAES D. SMITH M. (1998) | 3964 | 4308 |
| PENMAN H.L. NATURAL EVAPORATION FROM OPEN WATER BARE SOIL AND GRASS (1948) | 3880 | 3979 |
| Knowledge Base 2: KB 2: Methods for high-throughput sequencing/analysis (n = 2094, density =3.16) | ||
| PARKS D.H. IMELFORT M. SKENNERTON C.T. HUGENHOLTZ P. TYSON G.W. CHECKM: ASSESSING THE QUALITY OF MICROBIAL GENOMES RECOVERED FROM ISOLATES SINGLE C… | 7449 | 7452 |
| EDGAR R.C. SEARCH AND CLUSTERING ORDERS OF MAGNITUDE FASTER THAN BLAST (2010) | 4790 | 4790 |
| LANGMEAD B. SALZBERG S.L. FAST GAPPED-READ ALIGNMENT WITH BOWTIE 2 (2012) | 2705 | 2709 |
| BOLGER A.M. LOHSE M. USADEL B. TRIMMOMATIC: A FLEXIBLE TRIMMER FOR ILLUMINA SEQUENCE DATA (2014) | 2667 | 2683 |
| LOMBARD V. GOLACONDA RAMULU H. DRULA E. COUTINHO P.M. HENRISSAT B. THE CARBOHYDRATE-ACTIVE ENZYMES DATABASE (CAZY) | 2364 | 2364 |
| SEEMANN T. PROKKA: RAPID PROKARYOTIC GENOME ANNOTATION (2014) | 2306 | 2306 |
| KANG D.D. FROULA J. EGAN R. WANG Z. METABAT AN EFFICIENT TOOL FOR ACCURATELY RECONSTRUCTING SINGLE GENOMES FROM COMPLEX MICROBIAL COMMUNITIES (2015) | 2177 | 2177 |
| YIN Y. MAO X. YANG J. CHEN X. MAO F. XU Y. DBCAN: A WEB RESOURCE FOR AUTOMATED CARBOHYDRATE-ACTIVE ENZYME ANNOTATION (2012) | 2120 | 2120 |
| LETUNIC I. BORK P. INTERACTIVE TREE OF LIFE (ITOL) | 1942 | 1942 |
| KANEHISA M. GOTO S. KEGG: KYOTO ENCYCLOPEDIA OF GENES AND GENOMES (2000) | 1864 | 1864 |
| Knowledge Base 3: KB 3: Isotope hydrology, water age distribution (n = 1962, density =4.75) | ||
| MCGUIRE K.J. MCDONNELL J.J. A REVIEW AND EVALUATION OF CATCHMENT TRANSIT TIME MODELING (2006) | 5019 | 5223 |
| HARMAN C.J. TIME-VARIABLE TRANSIT TIME DISTRIBUTIONS AND TRANSPORT: THEORY AND APPLICATION TO STORAGE-DEPENDENT TRANSPORT OF CHLORIDE IN A WATERSHE… | 3555 | 3713 |
| TETZLAFF D. BIRKEL C. DICK J. GERIS J. SOULSBY C. STORAGE DYNAMICS IN HYDROPEDOLOGICAL UNITS CONTROL HILLSLOPE CONNECTIVITY RUNOFF GENERATION AND T… | 2457 | 2610 |
| MCGUIRE K.J. MCDONNELL J.J. WEILER M. KENDALL C. MCGLYNN B.L. WELKER J.M. SEIBERT J. THE ROLE OF TOPOGRAPHY ON CATCHMENT-SCALE WATER RESIDENCE TIME… | 2266 | 2354 |
| BOTTER G. BERTUZZO E. RINALDO A. CATCHMENT RESIDENCE AND TRAVEL TIME DISTRIBUTIONS: THE MASTER EQUATION (2011) | 2257 | 2370 |
| JASECHKO S. KIRCHNER J.W. WELKER J.M. MCDONNELL J.J. SUBSTANTIAL PROPORTION OF GLOBAL STREAMFLOW LESS THAN THREE MONTHS OLD (2016) | 2254 | 2323 |
| KIRCHNER J.W. FENG X. NEAL C. FRACTAL STREAM CHEMISTRY AND ITS IMPLICATIONS FOR CONTAMINANT TRANSPORT IN CATCHMENTS (2000) | 2251 | 2309 |
| HRACHOWITZ M. SAVENIJE H. BOGAARD T.A. TETZLAFF D. SOULSBY C. WHAT CAN FLUX TRACKING TEACH US ABOUT WATER AGE DISTRIBUTION PATTERNS AND THEIR TEMPO… | 2062 | 2282 |
| BOTTER G. BERTUZZO E. RINALDO A. TRANSPORT IN THE HYDROLOGIC RESPONSE: TRAVEL TIME DISTRIBUTIONS SOIL MOISTURE DYNAMICS AND THE OLD WATER PARADOX (… | 2029 | 2142 |
| KLAUS J. MCDONNELL J.J. HYDROGRAPH SEPARATION USING STABLE ISOTOPES: REVIEW AND EVALUATION (2013) | 2019 | 2103 |
| Knowledge Base 4: KB 4: Soil moisture estimates (n = 1832, density =3.57) | ||
| WAGNER W. LEMOINE G. ROTT H. A METHOD FOR ESTIMATING SOIL MOISTURE FROM ERS SCATTEROMETER AND SOIL DATA (1999) | 5102 | 5470 |
| NJOKU E.G. JACKSON T.J. LAKSHMI V. CHAN T.K. NGHIEM S.V. SOIL MOISTURE RETRIEVAL FROM AMSR-E (2003) | 1955 | 2135 |
| OWE M. DE JEU R. HOLMES T. MULTISENSOR HISTORICAL CLIMATOLOGY OF SATELLITE-DERIVED GLOBAL LAND SURFACE MOISTURE (2008) | 1767 | 1950 |
| REICHLE R.H. KOSTER R.D. BIAS REDUCTION IN SHORT RECORDS OF SATELLITE SOIL MOISTURE (2004) | 1759 | 1906 |
| NAEIMI V. SCIPAL K. BARTALIS Z. HASENAUER S. WAGNER W. AN IMPROVED SOIL MOISTURE RETRIEVAL ALGORITHM FOR ERS AND METOP SCATTEROMETER OBSERVATIONS (… | 1729 | 1772 |
| ENTEKHABI D. NJOKU E.G. O’NEILL P.E. KELLOGG K.H. CROW W.T. EDELSTEIN W.N. ENTIN J.K. JOHNSON J. THE SOIL MOISTURE ACTIVE PASSIVE (SMAP) | 1275 | 1298 |
| BROCCA L. MELONE F. MORAMARCO T. WAGNER W. NAEIMI V. BARTALIS Z. HASENAUER S. IMPROVING RUNOFF PREDICTION THROUGH THE ASSIMILATION OF THE ASCAT SOI… | 1268 | 1370 |
| STOFFELEN A. TOWARD THE TRUE NEAR-SURFACE WIND SPEED: ERROR MODELING AND CALIBRATION USING TRIPLE COLLOCATION (1998) | 1224 | 1277 |
| ALBERGEL C. DE ROSNAY P. GRUHIER C. MUÑOZ-SABATER J. HASENAUER S. ISAKSEN L. KERR Y. WAGNER W. EVALUATION OF REMOTELY SENSED AND MODELLED SOIL MOIS… | 899 | 919 |
| ENTEKHABI D. REICHLE R.H. KOSTER R.D. CROW W.T. PERFORMANCE METRICS FOR SOIL MOISTURE RETRIEVALS AND APPLICATION REQUIREMENTS (2010) | 870 | 917 |
| Knowledge Base 5: KB 5: BIM adoption (n = 1241, density =4.86) | ||
| BRYDE D. BROQUETAS M. VOLM J.M. THE PROJECT BENEFITS OF BUILDING INFORMATION MODELLING (BIM) | 4368 | 4371 |
| EADIE R. BROWNE M. ODEYINKA H. MCKEOWN C. MCNIFF S. BIM IMPLEMENTATION THROUGHOUT THE UK CONSTRUCTION PROJECT LIFECYCLE: AN ANALYSIS (2013) | 3538 | 3538 |
| AZHAR S. BUILDING INFORMATION MODELING (BIM) | 3038 | 3038 |
| SUCCAR B. BUILDING INFORMATION MODELLING FRAMEWORK: A RESEARCH AND DELIVERY FOUNDATION FOR INDUSTRY STAKEHOLDERS (2009) | 2499 | 2499 |
| GU N. LONDON K. UNDERSTANDING AND FACILITATING BIM ADOPTION IN THE AEC INDUSTRY (2010) | 2218 | 2218 |
| VOLK R. STENGEL J. SCHULTMANN F. BUILDING INFORMATION MODELING (BIM) | 2074 | 2074 |
| PORWAL A. HEWAGE K.N. BUILDING INFORMATION MODELING (BIM) | 1144 | 1144 |
| EASTMAN C. TEICHOLZ P. SACKS R. LISTON K. (2011) | 932 | 932 |
| WONG J.K.W. ZHOU J. ENHANCING ENVIRONMENTAL SUSTAINABILITY OVER BUILDING LIFE CYCLES THROUGH GREEN BIM: A REVIEW (2015) | 821 | 821 |
| BECERIK-GERBER B. JAZIZADEH F. LI N. CALIS G. APPLICATION AREAS AND DATA REQUIREMENTS FOR BIM-ENABLED FACILITIES MANAGEMENT (2012) | 785 | 785 |
| Knowledge Base 6: KB 6: Conceptual catchment modelling (n = 1112, density =5.94) | ||
| GUPTA H.V. KLING H. YILMAZ K.K. MARTINEZ G.F. DECOMPOSITION OF THE MEAN SQUARED ERROR AND NSE PERFORMANCE CRITERIA: IMPLICATIONS FOR IMPROVING HYDR… | 1477 | 2410 |
| KIRCHNER J.W. GETTING THE RIGHT ANSWERS FOR THE RIGHT REASONS: LINKING MEASUREMENTS ANALYSES AND MODELS TO ADVANCE THE SCIENCE OF HYDROLOGY (2006) | 1474 | 2400 |
| SCHOUPS G. VRUGT J.A. A FORMAL LIKELIHOOD FUNCTION FOR PARAMETER AND PREDICTIVE INFERENCE OF HYDROLOGIC MODELS WITH CORRELATED HETEROSCEDASTIC AND … | 1438 | 1538 |
| SEIBERT J. MCDONNELL J.J. ON THE DIALOG BETWEEN EXPERIMENTALIST AND MODELER IN CATCHMENT HYDROLOGY: USE OF SOFT DATA FOR MULTICRITERIA MODEL CALIBR… | 1106 | 1313 |
| GUPTA H.V. WAGENER T. LIU Y. RECONCILING THEORY WITH OBSERVATIONS: ELEMENTS OF A DIAGNOSTIC APPROACH TO MODEL EVALUATION (2008) | 1093 | 1158 |
| CLARK M.P. KAVETSKI D. FENICIA F. PURSUING THE METHOD OF MULTIPLE WORKING HYPOTHESES FOR HYDROLOGICAL MODELING (2011) | 1091 | 1227 |
| FENICIA F. KAVETSKI D. SAVENIJE H.H.G. ELEMENTS OF A FLEXIBLE APPROACH FOR CONCEPTUAL HYDROLOGICAL MODELING: 1. MOTIVATION AND THEORETICAL DEVELOPM… | 968 | 1019 |
| SAMANIEGO L. KUMAR R. ATTINGER S. MULTISCALE PARAMETER REGIONALIZATION OF A GRID-BASED HYDROLOGIC MODEL AT THE MESOSCALE (2010) | 925 | 1224 |
| GHARARI S. HRACHOWITZ M. FENICIA F. GAO H. SAVENIJE H.H.G. USING EXPERT KNOWLEDGE TO INCREASE REALISM IN ENVIRONMENTAL SYSTEM MODELS CAN DRAMATICAL… | 921 | 1010 |
| EUSER T. WINSEMIUS H.C. HRACHOWITZ M. FENICIA F. UHLENBROOK S. SAVENIJE H.H.G. A FRAMEWORK TO ASSESS THE REALISM OF MODEL STRUCTURES USING HYDROLOG… | 850 | 877 |
| Knowledge Base 7: KB 7: Suberin synthesis, metabolic pathway (n = 819, density =7.56) | ||
| POLLARD M. BEISSON F. LI Y. OHLROGGE J.B. BUILDING LIPID BARRIERS: BIOSYNTHESIS OF CUTIN AND SUBERIN (2008) | 1363 | 1389 |
| SAMUELS L. KUNST L. JETTER R. SEALING PLANT SURFACES: CUTICULAR WAX FORMATION BY EPIDERMAL CELLS (2008) | 1039 | 1042 |
| YADAV V. MOLINA I. RANATHUNGE K. CASTILLO I.Q. ROTHSTEIN S.J. REED J.W. ABCG TRANSPORTERS ARE REQUIRED FOR SUBERIN AND POLLEN WALL EXTRACELLULAR BA… | 932 | 945 |
| BIRD D. BEISSON F. BRIGHAM A. SHIN J. GREER S. JETTER R. KUNST L. SAMUELS L. CHARACTERIZATION OF ARABIDOPSIS ABCG11/WBC11 AN ATP BINDING CASSETTE (… | 734 | 741 |
| MOLINA I. LI-BEISSON Y. BEISSON F. OHLROGGE J.B. POLLARD M. IDENTIFICATION OF AN ARABIDOPSIS FERULOYL-COENZYME A TRANSFERASE REQUIRED FOR SUBERIN S… | 642 | 645 |
| SEO P.J. LEE S.B. SUH M.C. PARK M.J. GO Y.S. PARK C.M. THE MYB96 TRANSCRIPTION FACTOR REGULATES CUTICULAR WAX BIOSYNTHESIS UNDER DROUGHT CONDITIONS… | 596 | 602 |
| BEISSON F. LI Y. BONAVENTURE G. POLLARD M. OHLROGGE J.B. THE ACYLTRANSFERASE GPAT5 IS REQUIRED FOR THE SYNTHESIS OF SUBERIN IN SEED COAT AND ROOT O… | 590 | 599 |
| BEISSON F. LI-BEISSON Y. POLLARD M. SOLVING THE PUZZLES OF CUTIN AND SUBERIN POLYMER BIOSYNTHESIS (2012) | 586 | 593 |
| VISHWANATH S.J. DELUDE C. DOMERGUE F. ROWLAND O. SUBERIN: BIOSYNTHESIS REGULATION AND POLYMER ASSEMBLY OF A PROTECTIVE EXTRACELLULAR BARRIER (2015) | 584 | 587 |
| BERNARDS M.A. DEMYSTIFYING SUBERIN (2002) | 568 | 575 |
| Knowledge Base 8: KB 8: Security constrained optimal power flow (n = 764, density =4.92) | ||
| NICK M. CHERKAOUI R. PAOLONE M. OPTIMAL ALLOCATION OF DISPERSED ENERGY STORAGE SYSTEMS IN ACTIVE DISTRIBUTION NETWORKS FOR ENERGY BALANCE AND GRID … | 980 | 984 |
| BAI X. WEI H. FUJISAWA K. WANG Y. SEMIDEFINITE PROGRAMMING FOR OPTIMAL POWER FLOW PROBLEMS (2008) | 821 | 821 |
| LAVAEI J. LOW S.H. ZERO DUALITY GAP IN OPTIMAL POWER FLOW PROBLEM (2012) | 751 | 751 |
| COFFRIN C. HIJAZI H.L. VAN HENTENRYCK P. THE QC RELAXATION: A THEORETICAL AND COMPUTATIONAL STUDY ON OPTIMAL POWER FLOW (2016) | 577 | 577 |
| JABR R.A. RADIAL DISTRIBUTION LOAD FLOW USING CONIC PROGRAMMING (2006) | 536 | 536 |
| MADANI R. SOJOUDI S. LAVAEI J. CONVEX RELAXATION FOR OPTIMAL POWER FLOW PROBLEM: MESH NETWORKS (2015) | 485 | 485 |
| KOCUK B. DEY S.S. SUN X.A. STRONG SOCP RELAXATIONS FOR THE OPTIMAL POWER FLOW PROBLEM (2016) | 482 | 482 |
| MOLZAHN D.K. HISKENS I.A. SPARSITY-EXPLOITING MOMENT-BASED RELAXATIONS OF THE OPTIMAL POWER FLOW PROBLEM (2015) | 463 | 463 |
| MOLZAHN D.K. HOLZER J.T. LESIEUTRE B.C. DEMARCO C.L. IMPLEMENTATION OF A LARGE-SCALE OPTIMAL POWER FLOW SOLVER BASED ON SEMIDEFINITE PROGRAMMING (2… | 460 | 460 |
| ZAKERI B. SYRI S. ELECTRICAL ENERGY STORAGE SYSTEMS: A COMPARATIVE LIFE CYCLE COST ANALYSIS (2015) | 401 | 401 |
In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).
\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]
The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.
This is arguably the more interesting part. Here, we identify the
literature’s current knowledge frontier by carrying out a bibliographic
coupling analysis of the publications in our corpus. This measure uses
bibliographical information of publications to establish a similarity
relationship between them. Again, method details to be found in the tab
Technical description. As you will see, we identify the
main research area, but also a set of adjacent research areas with some
theoretical/methodological/application overlap.
To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.
| label | AU | PY | TI | dgr_int | TC | TC_year |
|---|---|---|---|---|---|---|
| Research Area 1: RA 1: Evapotranspiration estimates (n = 1415, density =0.34) | ||||||
| RA 1: Evapotranspiration estimates | ZHANG K;KIMBALL JS;RUN… | 2016 | A REVIEW OF REMOTE SENSING BASED ACTUAL EVAPOTRANSPIRATION ESTIMATION | 18.25 | 240 | 40.00 |
| RA 1: Evapotranspiration estimates | FISHER JB;MELTON F;MID… | 2017 | THE FUTURE OF EVAPOTRANSPIRATION: GLOBAL REQUIREMENTS FOR ECOSYSTEM FUNCTIONING, CARBON AND CLIMATE FEEDBACKS, AGRICULTURA… | 11.90 | 348 | 69.60 |
| RA 1: Evapotranspiration estimates | MARTENS B;MIRALLES DG;… | 2017 | GLEAM V3: SATELLITE-BASED LAND EVAPORATION AND ROOT-ZONE SOIL MOISTURE | 4.78 | 755 | 151.00 |
| RA 1: Evapotranspiration estimates | MIRALLES DG;JIMÉNEZ C;… | 2016 | THE WACMOS-ET PROJECT - PART 2: EVALUATION OF GLOBAL TERRESTRIAL EVAPORATION DATA SETS | 13.75 | 184 | 30.67 |
| RA 1: Evapotranspiration estimates | MCCABE MF;ERSHADI A;JI… | 2016 | THE GEWEX LANDFLUX PROJECT: EVALUATION OF MODEL EVAPORATION USING TOWER-BASED AND GLOBALLY GRIDDED FORCING DATA | 16.02 | 104 | 17.33 |
| RA 1: Evapotranspiration estimates | ZHANG Y;KONG D;GAN R;C… | 2019 | COUPLED ESTIMATION OF 500 M AND 8-DAY RESOLUTION GLOBAL EVAPOTRANSPIRATION AND GROSS PRIMARY PRODUCTION IN 2002–2017 | 9.91 | 151 | 50.33 |
| RA 1: Evapotranspiration estimates | BHATTARAI N;SHAW SB;QU… | 2016 | EVALUATING FIVE REMOTE SENSING BASED SINGLE-SOURCE SURFACE ENERGY BALANCE MODELS FOR ESTIMATING DAILY EVAPOTRANSPIRATION I… | 16.69 | 83 | 13.83 |
| RA 1: Evapotranspiration estimates | SENAY GB;FRIEDRICHS M;… | 2016 | EVALUATING LANDSAT 8 EVAPOTRANSPIRATION FOR WATER USE MAPPING IN THE COLORADO RIVER BASIN | 10.51 | 115 | 19.17 |
| RA 1: Evapotranspiration estimates | WESTERLING AL | 2016 | INCREASING WESTERN US FOREST WILDFIRE ACTIVITY: SENSITIVITY TO CHANGES IN THE TIMING OF SPRING | 2.08 | 558 | 93.00 |
| RA 1: Evapotranspiration estimates | HOBBINS MT;WOOD A;MCEV… | 2016 | THE EVAPORATIVE DEMAND DROUGHT INDEX. PART I: LINKING DROUGHT EVOLUTION TO VARIATIONS IN EVAPORATIVE DEMAND | 8.30 | 135 | 22.50 |
| Research Area 2: RA 2: Characterisation of microbial communities (n = 1347, density =0.26) | ||||||
| RA 2: Characterisation of microbial communities | PARADA AE;NEEDHAM DM;F… | 2016 | EVERY BASE MATTERS: ASSESSING SMALL SUBUNIT RRNA PRIMERS FOR MARINE MICROBIOMES WITH MOCK COMMUNITIES, TIME SERIES AND GLO… | 9.43 | 1174 | 195.67 |
| RA 2: Characterisation of microbial communities | PASOLLI E;ASNICAR F;MA… | 2019 | EXTENSIVE UNEXPLORED HUMAN MICROBIOME DIVERSITY REVEALED BY OVER 150,000 GENOMES FROM METAGENOMES SPANNING AGE, GEOGRAPHY,… | 12.72 | 481 | 160.33 |
| RA 2: Characterisation of microbial communities | ALMEIDA A;MITCHELL AL;… | 2019 | A NEW GENOMIC BLUEPRINT OF THE HUMAN GUT MICROBIOTA | 11.74 | 455 | 151.67 |
| RA 2: Characterisation of microbial communities | PARKS DH;CHUVOCHINA M;… | 2018 | A STANDARDIZED BACTERIAL TAXONOMY BASED ON GENOME PHYLOGENY SUBSTANTIALLY REVISES THE TREE OF LIFE | 4.34 | 1082 | 270.50 |
| RA 2: Characterisation of microbial communities | ZHANG H;YOHE T;HUANG L… | 2018 | DBCAN2: A META SERVER FOR AUTOMATED CARBOHYDRATE-ACTIVE ENZYME ANNOTATION | 6.52 | 663 | 165.75 |
| RA 2: Characterisation of microbial communities | RIQUELME E;ZHANG Y;ZHA… | 2019 | TUMOR MICROBIOME DIVERSITY AND COMPOSITION INFLUENCE PANCREATIC CANCER OUTCOMES | 11.06 | 370 | 123.33 |
| RA 2: Characterisation of microbial communities | SIEBER CMK;PROBST AJ;S… | 2018 | RECOVERY OF GENOMES FROM METAGENOMES VIA A DEREPLICATION, AGGREGATION AND SCORING STRATEGY | 13.71 | 289 | 72.25 |
| RA 2: Characterisation of microbial communities | SONNENBURG ED;SMITS SA… | 2016 | DIET-INDUCED EXTINCTIONS IN THE GUT MICROBIOTA COMPOUND OVER GENERATIONS | 4.20 | 835 | 139.17 |
| RA 2: Characterisation of microbial communities | BAHRAM M;HILDEBRAND F;… | 2018 | STRUCTURE AND FUNCTION OF THE GLOBAL TOPSOIL MICROBIOME | 5.35 | 629 | 157.25 |
| RA 2: Characterisation of microbial communities | JAIN C;RODRIGUEZ-R LM;… | 2018 | HIGH THROUGHPUT ANI ANALYSIS OF 90K PROKARYOTIC GENOMES REVEALS CLEAR SPECIES BOUNDARIES | 3.01 | 892 | 223.00 |
| Research Area 3: RA 3: Water age distribution, store-age-selection function (n = 988, density =0.22) | ||||||
| RA 3: Water age distribution, store-age-selection function | KIRCHNER JW | 2016 | AGGREGATION IN ENVIRONMENTAL SYSTEMS-PART 1: SEASONAL TRACER CYCLES QUANTIFY YOUNG WATER FRACTIONS, BUT NOT MEAN TRANSIT T… | 8.03 | 183 | 30.50 |
| RA 3: Water age distribution, store-age-selection function | SPRENGER M;LEISTERT H;… | 2016 | ILLUMINATING HYDROLOGICAL PROCESSES AT THE SOIL-VEGETATION-ATMOSPHERE INTERFACE WITH WATER STABLE ISOTOPES | 4.40 | 233 | 38.83 |
| RA 3: Water age distribution, store-age-selection function | HRACHOWITZ M;BENETTIN … | 2016 | TRANSIT TIMES—THE LINK BETWEEN HYDROLOGY AND WATER QUALITY AT THE CATCHMENT SCALE | 6.68 | 132 | 22.00 |
| RA 3: Water age distribution, store-age-selection function | BENETTIN P;SOULSBY C;B… | 2017 | USING SAS FUNCTIONS AND HIGH-RESOLUTION ISOTOPE DATA TO UNRAVEL TRAVEL TIME DISTRIBUTIONS IN HEADWATER CATCHMENTS | 10.38 | 79 | 15.80 |
| RA 3: Water age distribution, store-age-selection function | KIRCHNER JW | 2016 | AGGREGATION IN ENVIRONMENTAL SYSTEMS-PART 2: CATCHMENT MEAN TRANSIT TIMES AND YOUNG WATER FRACTIONS UNDER HYDROLOGIC NONST… | 7.77 | 99 | 16.50 |
| RA 3: Water age distribution, store-age-selection function | SPRENGER M;STUMPP C;WE… | 2019 | THE DEMOGRAPHICS OF WATER: A REVIEW OF WATER AGES IN THE CRITICAL ZONE | 7.73 | 98 | 32.67 |
| RA 3: Water age distribution, store-age-selection function | SPRENGER M;SEEGER S;BL… | 2016 | TRAVEL TIMES IN THE VADOSE ZONE: VARIABILITY IN SPACE AND TIME | 7.80 | 76 | 12.67 |
| RA 3: Water age distribution, store-age-selection function | SPRENGER M;TETZLAFF D;… | 2017 | EVAPORATION FRACTIONATION IN A PEATLAND DRAINAGE NETWORK AFFECTS STREAM WATER ISOTOPE COMPOSITION | 7.87 | 75 | 15.00 |
| RA 3: Water age distribution, store-age-selection function | FOWLER KJA;PEEL MC;WES… | 2016 | SIMULATING RUNOFF UNDER CHANGING CLIMATIC CONDITIONS: REVISITING AN APPARENT DEFICIENCY OF CONCEPTUAL RAINFALL-RUNOFF MODELS | 5.29 | 98 | 16.33 |
| RA 3: Water age distribution, store-age-selection function | BERGHUIJS WR;KIRCHNER JW | 2017 | THE RELATIONSHIP BETWEEN CONTRASTING AGES OF GROUNDWATER AND STREAMFLOW | 10.26 | 49 | 9.80 |
| Research Area 4: RA 4: Soil moisture (n = 902, density =0.24) | ||||||
| RA 4: Soil moisture | PENG J;LOEW A;MERLIN O… | 2017 | A REVIEW OF SPATIAL DOWNSCALING OF SATELLITE REMOTELY SENSED SOIL MOISTURE | 6.94 | 301 | 60.20 |
| RA 4: Soil moisture | DORIGO W;WAGNER W;ALBE… | 2017 | ESA CCI SOIL MOISTURE FOR IMPROVED EARTH SYSTEM UNDERSTANDING: STATE-OF-THE ART AND FUTURE DIRECTIONS | 4.14 | 504 | 100.80 |
| RA 4: Soil moisture | COLLIANDER A;JACKSON T… | 2017 | VALIDATION OF SMAP SURFACE SOIL MOISTURE PRODUCTS WITH CORE VALIDATION SITES | 4.36 | 376 | 75.20 |
| RA 4: Soil moisture | HAJJ ME;BAGHDADI N;ZRI… | 2017 | SYNERGIC USE OF SENTINEL-1 AND SENTINEL-2 IMAGES FOR OPERATIONAL SOIL MOISTURE MAPPING AT HIGH SPATIAL RESOLUTION OVER AGR… | 6.21 | 171 | 34.20 |
| RA 4: Soil moisture | KERR YH;AL-YAARI A;ROD… | 2016 | OVERVIEW OF SMOS PERFORMANCE IN TERMS OF GLOBAL SOIL MOISTURE MONITORING AFTER SIX YEARS IN OPERATION | 4.83 | 186 | 31.00 |
| RA 4: Soil moisture | BROCCA L;CIABATTA L;MA… | 2017 | SOIL MOISTURE FOR HYDROLOGICAL APPLICATIONS: OPEN QUESTIONS AND NEW OPPORTUNITIES | 4.93 | 162 | 32.40 |
| RA 4: Soil moisture | KIM H;PARINUSSA R;KONI… | 2018 | GLOBAL-SCALE ASSESSMENT AND COMBINATION OF SMAP WITH ASCAT (ACTIVE) AND AMSR2 (PASSIVE) SOIL MOISTURE PRODUCTS | 7.77 | 99 | 24.75 |
| RA 4: Soil moisture | CUI C;XU J;ZENG J;CHEN… | 2018 | SOIL MOISTURE MAPPING FROM SATELLITES: AN INTERCOMPARISON OF SMAP, SMOS, FY3B, AMSR2, AND ESA CCI OVER TWO DENSE NETWORK R… | 7.33 | 92 | 23.00 |
| RA 4: Soil moisture | BAGHDADI N;HAJJ ME;ZRI… | 2017 | CALIBRATION OF THE WATER CLOUD MODEL AT C-BAND FOR WINTER CROP FIELDS AND GRASSLANDS | 6.16 | 106 | 21.20 |
| RA 4: Soil moisture | BAUER-MARSCHALLINGER B… | 2019 | TOWARD GLOBAL SOIL MOISTURE MONITORING WITH SENTINEL-1: HARNESSING ASSETS AND OVERCOMING OBSTACLES | 4.87 | 127 | 42.33 |
| Research Area 5: RA 5: TSO-DSO coordination (n = 774, density =0.12) | ||||||
| RA 5: TSO-DSO coordination | KOCUK B;DEY SS;ANDY SUN X | 2016 | STRONG SOCP RELAXATIONS FOR THE OPTIMAL POWER FLOW PROBLEM | 4.34 | 145 | 24.17 |
| RA 5: TSO-DSO coordination | WONG LA;RAMACHANDARAMU… | 2019 | REVIEW ON THE OPTIMAL PLACEMENT, SIZING AND CONTROL OF AN ENERGY STORAGE SYSTEM IN THE DISTRIBUTION NETWORK | 3.02 | 140 | 46.67 |
| RA 5: TSO-DSO coordination | HAIDER HT;SEE OH;ELMEN… | 2016 | A REVIEW OF RESIDENTIAL DEMAND RESPONSE OF SMART GRID | 1.23 | 303 | 50.50 |
| RA 5: TSO-DSO coordination | LI P;JI H;WANG C;ZHAO … | 2017 | COORDINATED CONTROL METHOD OF VOLTAGE AND REACTIVE POWER FOR ACTIVE DISTRIBUTION NETWORKS BASED ON SOFT OPEN POINT | 1.86 | 188 | 37.60 |
| RA 5: TSO-DSO coordination | LI P;JI H;WANG C;ZHAO … | 2019 | OPTIMAL OPERATION OF SOFT OPEN POINTS IN ACTIVE DISTRIBUTION NETWORKS UNDER THREE-PHASE UNBALANCED CONDITIONS | 3.58 | 93 | 31.00 |
| RA 5: TSO-DSO coordination | SABOORI H;HEMMATI R;GH… | 2017 | ENERGY STORAGE PLANNING IN ELECTRIC POWER DISTRIBUTION NETWORKS – A STATE-OF-THE-ART REVIEW | 2.36 | 122 | 24.40 |
| RA 5: TSO-DSO coordination | NICK M;CHERKAOUI R;PAO… | 2018 | OPTIMAL PLANNING OF DISTRIBUTED ENERGY STORAGE SYSTEMS IN ACTIVE DISTRIBUTION NETWORKS EMBEDDING GRID RECONFIGURATION | 3.11 | 92 | 23.00 |
| RA 5: TSO-DSO coordination | YANG Z;ZHONG H;BOSE A;… | 2018 | A LINEARIZED OPF MODEL WITH REACTIVE POWER AND VOLTAGE MAGNITUDE: A PATHWAY TO IMPROVE THE MW-ONLY DC OPF | 1.89 | 148 | 37.00 |
| RA 5: TSO-DSO coordination | BAI L;JIANG T;LI F;CHE… | 2018 | DISTRIBUTED ENERGY STORAGE PLANNING IN SOFT OPEN POINT BASED ACTIVE DISTRIBUTION NETWORKS INCORPORATING NETWORK RECONFIGUR… | 2.82 | 96 | 24.00 |
| RA 5: TSO-DSO coordination | GIANNITRAPANI A;PAOLET… | 2017 | OPTIMAL ALLOCATION OF ENERGY STORAGE SYSTEMS FOR VOLTAGE CONTROL IN LV DISTRIBUTION NETWORKS | 2.43 | 109 | 21.80 |
| Research Area 6: RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis (n = 617, density =0.16) | ||||||
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | BARBERON M;VERMEER JEM… | 2016 | ADAPTATION OF ROOT FUNCTION BY NUTRIENT-INDUCED PLASTICITY OF ENDODERMAL DIFFERENTIATION | 1.86 | 253 | 42.17 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | FICH EA;SEGERSON NA;RO… | 2016 | THE PLANT POLYESTER CUTIN: BIOSYNTHESIS, STRUCTURE, AND BIOLOGICAL ROLES | 2.65 | 178 | 29.67 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | LASHBROOKE J;COHEN H;L… | 2016 | MYB107 AND MYB9 HOMOLOGS REGULATE SUBERIN DEPOSITION IN ANGIOSPERMS | 3.55 | 93 | 15.50 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | LEE SB;KIM HU;SUH MC | 2016 | MYB94 AND MYB96 ADDITIVELY ACTIVATE CUTICULAR WAX BIOSYNTHESIS IN ARABIDOPSIS | 4.43 | 74 | 12.33 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | JI Z;JI H | 2016 | TSCAN: PSEUDO-TIME RECONSTRUCTION AND EVALUATION IN SINGLE-CELL RNA-SEQ ANALYSIS | 1.14 | 251 | 41.83 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | HWANG J-U;SONG W-Y;HON… | 2016 | PLANT ABC TRANSPORTERS ENABLE MANY UNIQUE ASPECTS OF A TERRESTRIAL PLANT’S LIFESTYLE | 1.40 | 183 | 30.50 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | DO THT;MARTINOIA E;LEE Y | 2018 | FUNCTIONS OF ABC TRANSPORTERS IN PLANT GROWTH AND DEVELOPMENT | 2.88 | 86 | 21.50 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | LEGAY S;GUERRIERO G;AN… | 2016 | MDMYB93 IS A REGULATOR OF SUBERIN DEPOSITION IN RUSSETED APPLE FRUIT SKINS | 3.59 | 68 | 11.33 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | GOU M;HOU G;YANG H;ZHA… | 2017 | THE MYB107 TRANSCRIPTION FACTOR POSITIVELY REGULATES SUBERIN BIOSYNTHESIS | 4.33 | 54 | 10.80 |
| RA 6: Plant adaptation, physiology, cell wall synthesis, suberin biosynthesis | FERNÁNDEZ V;GUZMÁN-DEL… | 2016 | CUTICLE STRUCTURE IN RELATION TO CHEMICAL COMPOSITION: RE-ASSESSING THE PREVAILING MODEL | 1.44 | 128 | 21.33 |
| Research Area 7: RA 7: Benefits of BIM through use cases (n = 478, density =0.59) | ||||||
| RA 7: Benefits of BIM through use cases | GHAFFARIANHOSEINI A;TO… | 2017 | BUILDING INFORMATION MODELLING (BIM) UPTAKE: CLEAR BENEFITS, UNDERSTANDING ITS IMPLEMENTATION, RISKS AND CHALLENGES | 7.25 | 268 | 53.60 |
| RA 7: Benefits of BIM through use cases | ZHAO X | 2017 | A SCIENTOMETRIC REVIEW OF GLOBAL BIM RESEARCH: ANALYSIS AND VISUALIZATION | 8.89 | 206 | 41.20 |
| RA 7: Benefits of BIM through use cases | LU Y;WU Z;CHANG R;LI Y | 2017 | BUILDING INFORMATION MODELING (BIM) FOR GREEN BUILDINGS: A CRITICAL REVIEW AND FUTURE DIRECTIONS | 6.57 | 225 | 45.00 |
| RA 7: Benefits of BIM through use cases | HE Q;WANG G;LUO L;SHI … | 2017 | MAPPING THE MANAGERIAL AREAS OF BUILDING INFORMATION MODELING (BIM) USING SCIENTOMETRIC ANALYSIS | 7.78 | 174 | 34.80 |
| RA 7: Benefits of BIM through use cases | SANTOS R;COSTA AA;GRILO A | 2017 | BIBLIOMETRIC ANALYSIS AND REVIEW OF BUILDING INFORMATION MODELLING LITERATURE PUBLISHED BETWEEN 2005 AND 2015 | 5.44 | 173 | 34.60 |
| RA 7: Benefits of BIM through use cases | ORAEE M;HOSSEINI MR;PA… | 2017 | COLLABORATION IN BIM-BASED CONSTRUCTION NETWORKS: A BIBLIOMETRIC-QUALITATIVE LITERATURE REVIEW | 5.07 | 163 | 32.60 |
| RA 7: Benefits of BIM through use cases | LIU Y;VAN NEDERVEEN S;… | 2017 | UNDERSTANDING EFFECTS OF BIM ON COLLABORATIVE DESIGN AND CONSTRUCTIONAN EMPIRICAL STUDY IN CHINA | 3.74 | 188 | 37.60 |
| RA 7: Benefits of BIM through use cases | ZOU Y;KIVINIEMI A;JONE… | 2017 | A REVIEW OF RISK MANAGEMENT THROUGH BIM AND BIM-RELATED TECHNOLOGIES | 4.71 | 149 | 29.80 |
| RA 7: Benefits of BIM through use cases | TAY YWD;PANDA B;PAUL S… | 2017 | 3D PRINTING TRENDS IN BUILDING AND CONSTRUCTION INDUSTRY: A REVIEW | 1.99 | 325 | 65.00 |
| RA 7: Benefits of BIM through use cases | KHAJAVI SH;MOTLAGH NH;… | 2019 | DIGITAL TWIN: VISION, BENEFITS, BOUNDARIES, AND CREATION FOR BUILDINGS | 5.38 | 105 | 35.00 |
In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.
\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]
Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).
\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]
More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.
All results are preliminary so far…